• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.499-502
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• 1998

Most popular disk block replacement polices are LRU(Least Recently Used)policy and LFU(Least Frequently Used)policy. The LRU policy replaces blocks according to the most recent reference without considering the frequency of reference. The LFU policy replaces blocks according to the frequency of reference without considering the recently of the reference. In this thesis, a policy called LFR(least Frequently Use & Not Used Recently) disk block replacement policy is presented. The LFR policy subsumes the LFU policy and the NUR policy. The spectrum of the LFR policy exists between the LFU policy and the NUR policy because we co give different weight to each reference of a block. The implementation shows LFR policy outperforms the previously implemente LRU policy.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04a
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• pp.12-14
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• 2000

소형의 이동 컴퓨터 시스템이 발전하면서 프로세서의 전력 소모(energy dissipation)가 중요한 이슈가 되고 있다. 현재 대부분의 프로세서들은 성능 향상을 위해 캐쉬를 사용하고 있고 이것은 프로세서내의 많은 비율의 전력을 소모한다. 따라서 저 전력 프로세서를 설계하기 위해서는 내장 캐쉬(on-chip cache)의 전력 소모를 줄이는 것이 중요하다. 본 논문은 캐쉬 대체 전략으로 현재 많이 사용되는 LRU(Least Recently Used) 방식을 LFU(Least Frequently Used), LFUT(LFU with Threshold), FIFO(First In First Out) 방식과 관련 효율적 측면에서 비교 분석 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.10-12
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• 2001

웹에서 도큐먼트 재배치 정책은 캐쉬(cache)성능을 향상시키기 위한 방법중의 하나이다. 이 방법을 웹 캐쉬 공간이 한정되어 있으며 새로운 도큐먼트를 위한 공간을 만들기 위해 어느 도큐먼트를 축출(remove)[2]할 것인가를 결정하고 새로운 도큐먼트를 갱신(update)[6]하기 위한 방법을 제공한다. 도큐먼트 재배치 정책으로는 LRU(Least Recently Used), LFU(Least Frequently Used)등과 같은 방법이 보편적을 사용되고 있으나, 웹에 적용하기에는 몇 가지 단점이 있다. 본 논문에서는 LRU, LFU등의 도큐먼트 재배치 정책을 이용하면서도 웹에 적용하기 위해 몇 가지 단점을 보완한 LRFU(Least Recently/Frequently Used)[4]기법을 사용한다. 또한 본 논문에서는 인터넷(internet) 사용자의 지수적인(exponential) 증가와 이로 인한 병목현상(bottleneck)의 발생을 전제로 하여, 캐쉬성능을 향상시키기 위한 다각적인 시도로 지역성(locality), 일관성(consistency)[7][5], 확장성(scalability)[5]등의 문제에 관한 논의와 기존의 방법과는 다른 도큐먼트 재배치 정책에의 접근을 시도한다.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.1
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• pp.14-20
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• 2009

Recently, NAND flash memory is used not only for portable devices, but also for personal computers and server computers. Buffer cache replacement policies for the hard disks such as LRU and LFU are not good for NAND flash memories because they do not consider about the characteristics of NAND flash memory. CFLRU and its variants, CFLRU/C, CFLRU/E and DL-CFLRU/E(CFLRUs) are the buffer cache replacement policies considered about the characteristics of NAND flash memories, but their performances are not better than those of LRD. In this paper, we propose a new buffer cache replacement policy for NAND flash memory. Which is based on LFU and is taking into account the characteristics of NAND flash memory. And we estimate the performance of hit ratio and flush operation numbers. The proposed policy shows better hit ratio and the number of flush operation than any other policies.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1669-1679
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• 1996

In this paper, we address the problem of how to replace huffers in multimedia database systems with time-varying skewed data access. The access pattern in the multimedia database system to support audio-on-demand and video-on-demand services is generally skewed with a few popular objects. In addition the access pattem of the skewed objects has a time-varying property. In such situations, our analysis indicates that conventional LRU(least Recently Used) and LFU(Least Frequently Used) schemes for buffer replacement algorithm(ABRN:Adaptive Buffer Replacement using Neural suited. We propose a new buffer replacement algorithm(ABRN:Adaptive Buffer Replacement using Neural Networks)using a neural network for multimedia database systems with time-varying skewed data access. The major role of our neural network classifies multimedia objects into two classes:a hot set frequently accessed with great popularity and a cold set randomly accessed with low populsrity. For the classification, the inter-arrival time values of sample objects are employed to train the neural network.Our algorithm partitions buffers into two regions to combine the best roperties of LRU and LFU.One region, which contains the 핫셋 objects, is managed by LFU replacement and the other region , which contains the cold set objects , is managed by LRUreplacement.We performed simulation experiments in an actual environment with time-varying skewed data accsee to compare our algorithm to LRU, LFU, and LRU-k which is a variation of LRU. Simulation resuults indicate that our proposed algorthm provides better performance as compared to the other algorithms. Good performance of the neural network-based replacement scheme means that this new approach can be also suited as an alternative to the existing page replacement and prefetching algorithms in virtual memory systems.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.148-157
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• 2002

Caching in meta-search engines can improve the response time of users' request. We describe the cache scheme in our meta-search engine in terms of its architecture and operational flow. In particular, we propose a popularity-driven cache algorithm that utilizes popularities of queries to determine cached data to be purged. The popularity is a value that represents the normalized occurrence frequency of user queries. This paper presents how to collect popular queries and how to calculate query popularities. An empirical performance evaluation of the popularity-driven caching with the traditional schemes (i.e., least recently used (LRU) and least frequently used (LFU)) has been carried out on a collection of real data. In almost all cases, the proposed replacement policy outperforms LRU and LFU.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1113-1120
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• 2021

Content Central Network (CCN) appeared to improve network efficiency by transforming IP-based network into content name-based network structures. Each router performs caching mechanism to improve network efficiency in the CCN. And the cache replacement policy applied to the CCN router is an important factor that determines the overall performance of the CCN. Therefore various studies has been done relating to cache replacement policy of the CCN. In this paper, we proposed a cache replacement policy that improves the limitations of the LFU policy. The proposal algorithm applies real-time producer popularity-based variables. And through experiments, we proved that the proposed policy shows a better cache hit ratio than existing policies.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.469-478
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• 2001

In the virtual memory system, page replacement policy exerts a great influence on the performance of demand paging. There are LRU(Least Recently Used) and LFU (Least Frequently Used) as the typical replacement policies. The LRU policy performs effectively in many cases and adapts well to the changing workloads compared to other policies. It however cannot distinguish well between frequently and infrequently referenced pages. The LFU policy requires that the page with the smallest reference count be replaced. Though it considers all the references in the past, it cannot discriminate between references that occurred far back in the past and the more recent ones. Thus, it cannot adapt well to the changing workload. In this paper, we first analyze memory reference patterns of eight applications. The patterns show that the recently referenced pages or the frequently referenced pages are accessed continuously as the case may be. So it is rather hard to optimize page replacement scheme by using just one of the LRU or LFU policy. This paper makes an attempt to combine the advantages of the two policies and proposes a new page replacement policy. In the proposed policy, paging list is divided into two lists (LRU and LFU lists). By keeping the two lists in recency and reference frequency order respectively, we try to restrain the highly referenced pages in the past from being replaced by the LRU policy. Results from trace-driven simulations show that there exists points on the spectrum at which the proposed policy performs better than the previously known policies for the workloads we considered. Especially, we can see that our policy outperforms the existing ones in such applications that have reference patterns of re-accessing the frequently referenced pages in the past after some time.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.1-10
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• 2010

Recently heterogeneous storage system such as hybrid hard disk drive (H-HDD) combining flash memory and magnetic disk is launched, according as the read performance of NAND flash memory is enhanced as similar to that of hard disk drive (HDD) and the power consumption of NAND flash memory is reduced less than that of HDD. However, the read and write operations of NAND flash memory are slower than those of rotational disk. Besides, serious overheads are incurred on CPU and main memory in the case that intensive write requests to flash memory are repeatedly occurred. In this paper, we propose the Least Frequently Used-Hot scheme that replaces the data blocks whose reference frequency of read operation is low and update frequency of write operation is high, and the data flushing scheme that rearranges the data blocks into the multi-zone of the rotation disk. Experimental results show that the execution time of the proposed method is 38% faster than those of conventional LRU and LFU block replacement schemes in I/O performance aspect and the proposed method increases the life span of Non-Volatile Cache 40% higher than those of conventional LRU, LFU, FIFO block replacement schemes.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.233-236
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• 2002

본 논문은 인터넷상에서 다양한 매체를 이용한 서비스를 제공할 때 생길 수 있는 긴 사용자-서버간 지연, 엄청난 서버의 부하, 네트워크 자원의 비효율적 사용과 같은 문제점들을 위한 개선된 방법으로 사용자에 가까운 복수의 노드들을 두어 서버에서 전송된 데이터를 분산 저장하는 방법에 대해 다루고 있다. 새로운 분산 Proxy 기법은 VOD 서비스를 원하는 사용자들이 통일한 아이템에 대한 요청이 많은 서비스 패턴을 분석해서, 중복된 네트워크 부하는 줄이는 과정을 수행한다. 사용자가 요청한 영화는 서버에서 전송을 받는데 이때, HEN(Head-End-Node)에 구현된 여러 Proxy에 아이템의 일부를 나누어 저장하고 이에 대한 정보 보관과 제어를 SA(Switching Agent)가 하게 된다. 사용자가 서비스를 요청할 경우 SA의 제어 하에 분산 Proxy에 교호적으로 접속을 하여 저장되어 있는 부분적인 데이터들을 서비스 받도록 한다. 이때 Proxy에 새로운 데이터 블록을 저장할 때는 부족한 저장공간으로 인해 LRU(Least Recently Used), LFU(Least Frequently Used), 또는 이들을 복합한 Hybrid 정책을 사용한다.